Customer Segmentation Matrix

import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import numpy as np
from matplotlib.colors import LinearSegmentedColormap

np.random.seed(42)

# RFM-like customer data
segments = ['Champions', 'Loyal', 'Potential', 'New', 'At Risk', 'Lost']
metrics = ['Frequency', 'Monetary', 'Recency', 'Engagement', 'LTV', 'Satisfaction']

# Segment profiles
data = np.array([
    [0.95, 0.90, 0.95, 0.88, 0.92, 0.90],  # Champions
    [0.80, 0.75, 0.85, 0.72, 0.78, 0.82],  # Loyal
    [0.55, 0.50, 0.70, 0.60, 0.55, 0.65],  # Potential
    [0.30, 0.25, 0.90, 0.45, 0.20, 0.50],  # New
    [0.25, 0.35, 0.20, 0.30, 0.40, 0.35],  # At Risk
    [0.10, 0.15, 0.05, 0.08, 0.12, 0.15],  # Lost
])

df = pd.DataFrame(data, index=segments, columns=metrics)

# NEON coral colormap
neon_coral = LinearSegmentedColormap.from_list('neon_coral', ['#ffffff', '#F5B027', '#F5276C', '#9C2007'])

fig, ax = plt.subplots(figsize=(9, 6), facecolor='#ffffff')
ax.set_facecolor('#ffffff')

sns.heatmap(df, cmap=neon_coral, annot=True, fmt='.0%', linewidths=2, linecolor='#ffffff',
            vmin=0, vmax=1, annot_kws={'size': 11, 'fontweight': '600'},
            cbar_kws={'shrink': 0.8, 'label': 'Score'}, ax=ax)

ax.set_title('Customer Segment Analysis', color='#1f2937', fontsize=14, fontweight='bold', pad=15)
ax.tick_params(colors='#374151', labelsize=10)
ax.set_xticklabels(ax.get_xticklabels(), rotation=45, ha='right')

plt.tight_layout()
plt.show()